Summary

This notebook plots breakdowns of Germany transmission lineages over time (using only the assignment on the MCC trees).

Data and Method

  • GISAID tree until 2021-06-03 as initial tree.
  • The tree contains 541,000 ??? sequences.
  • The small branches are collapsed.
  • The tree is time-collibrated by TreeTime.
  • Sankoff algorithm is used to assign location (Germany and non-Germany) to inner vertices of the tree.

Sample breakdown (daily)

Number of genomes collected each day, coloured by the time since the age of the transmission lineage when the genome was collected (time from the oldest sampled genome in the lineage to the sampling time of the genome). Note that **only** genomes in transmission lineages are shown (no singletons).

Number of genomes collected each day, coloured by the time since the age of the transmission lineage when the genome was collected (time from the oldest sampled genome in the lineage to the sampling time of the genome). Note that only genomes in transmission lineages are shown (no singletons).

Number of genomes collected each day, coloured by the TMRCA of the transmission lineage. Note that **only** genomes in transmission lineages are shown (no singletons).

Number of genomes collected each day, coloured by the TMRCA of the transmission lineage. Note that only genomes in transmission lineages are shown (no singletons).

Sample breakdown into lineages (weekly)

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

The weekly sampling frequency of the 8 largest `r state` transmission lineages.

The weekly sampling frequency of the 8 largest r state transmission lineages.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured.

Lineage size breakdown of Germany genomes collected each week. The 8 largest lineages are coloured. 

## Error in maptools::unionSpatialPolygons(cp, attr[, region]): isTRUE(gpclibPermitStatus()) is not TRUE
## Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'match': object 'germany.f' not found
Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week. 

## Warning in xy.coords(x, y, xlabel, ylabel, log): 21 y values <= 0 omitted from
## logarithmic plot
Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Lineage size breakdown of Germany genomes collected each week.

Individual transmission lineage plots

Biggest transmission lineages

Illustration of the time course of the 50 largest Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 largest Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

cluster Pango.lineage sample_date lineage_seqs state
LIN-Germany-B.1.1.7-23859-20210602_DTA_MCC_1 B.1.1.7 2021-01-22 2718 North Rhine-Westphalia
LIN-Germany-B.1.1.7-23859-20210602_DTA_MCC_1 B.1.1.7 2021-01-22 2718 North Rhine-Westphalia
LIN-Germany-B.1.1.7-26624-20210602_DTA_MCC_1 B.1.1.7 2021-01-31 2575 Saxony
LIN-Germany-B.1.1.7-34110-20210602_DTA_MCC_1 B.1.1.7 2021-02-18 1983 Baden-Wurttemberg
LIN-Germany-B.1.1.7-29629-20210602_DTA_MCC_1 B.1.1.7 2021-01-25 1646 Thuringia
LIN-Germany-B.1.1.7-34109-20210602_DTA_MCC_1 B.1.1.7 2021-01-22 1556 Thuringia
LIN-Germany-B.1.1.7-7290-20210602_DTA_MCC_1 B.1.1.7 2021-01-02 1468 North Rhine-Westphalia
LIN-Germany-B.1.1.7-24120-20210602_DTA_MCC_1 B.1.1.7 2021-01-25 1296 Rhineland-Palatinate
LIN-Germany-B.1.1.7-31690-20210602_DTA_MCC_1 B.1.1.7 2021-02-05 922 Thuringia
LIN-Germany-B.1.1.7-31690-20210602_DTA_MCC_1 B.1.1.7 2021-02-05 922 Thuringia
LIN-Germany-B.1.1.7-31690-20210602_DTA_MCC_1 B.1.1.7 2021-02-05 922 Bavaria
LIN-Germany-B.1.1.7-31690-20210602_DTA_MCC_1 B.1.1.7 2021-02-05 922 Thuringia
LIN-Germany-B.1.1.7-55470-20210602_DTA_MCC_1 B.1.1.7 2021-01-22 767 North Rhine-Westphalia
LIN-Germany-B.1.1.7-33946-20210602_DTA_MCC_1 B.1.1.7 2021-02-08 635 Bavaria
LIN-Germany-B.1.1.7-35161-20210602_DTA_MCC_1 B.1.1.7 2021-01-19 608 Saxony
LIN-Germany-B.1.1.7-25980-20210602_DTA_MCC_1 B.1.1.7 2021-02-09 577 Saxony
LIN-Germany-B.1.1.7-63701-20210602_DTA_MCC_1 B.1.1.7 2021-02-11 520 Berlin
LIN-Germany-B.1.1.7-9569-20210602_DTA_MCC_1 B.1.1.7 2021-02-09 518 North Rhine-Westphalia
LIN-Germany-B.1.1.7-27729-20210602_DTA_MCC_1 B.1.1.7 2021-01-27 517 Thuringia
LIN-Germany-B.1.1.7-9106-20210602_DTA_MCC_1 B.1.1.7 2021-01-28 478 Baden-Wurttemberg
LIN-Germany-B.1.1.7-38045-20210602_DTA_MCC_1 B.1.1.7 2021-01-27 438 Rhineland-Palatinate
LIN-Germany-B.1.1.7-38114-20210602_DTA_MCC_1 B.1.1.7 2021-01-14 432 Baden-Wurttemberg
LIN-Germany-B.1.1.7-35231-20210602_DTA_MCC_1 B.1.1.7 2021-02-09 430
LIN-Germany-B.1.1.7-39671-20210602_DTA_MCC_1 B.1.1.7 2021-02-08 426 North Rhine-Westphalia
LIN-Germany-B.1.1.7-38575-20210602_DTA_MCC_1 B.1.1.7 2021-02-17 415 Berlin
LIN-Germany-B.1.160-20210602_DTA_MCC_1029 B.1.160 2020-11-13 378 Saarland
LIN-Germany-B.1.1.7-54961-20210602_DTA_MCC_1 B.1.1.7 2021-02-09 336 Bremen
LIN-Germany-B.1.1.7-54961-20210602_DTA_MCC_1 B.1.1.7 2021-02-09 336 Bremen
LIN-Germany-B.1.1.7-32894-20210602_DTA_MCC_1 B.1.1.7 2021-02-24 314 Thuringia
LIN-Germany-B.1.1.7-32894-20210602_DTA_MCC_1 B.1.1.7 2021-02-24 314 Thuringia
LIN-Germany-B.1.1.7-32894-20210602_DTA_MCC_1 B.1.1.7 2021-02-24 314 Thuringia
LIN-Germany-B.1.1.7-33722-20210602_DTA_MCC_1 B.1.1.7 2021-02-12 313 Saxony-Anhalt
LIN-Germany-B.1.1.7-33722-20210602_DTA_MCC_1 B.1.1.7 2021-02-12 313 Saxony-Anhalt
LIN-Germany-B.1.1.7-59513-20210602_DTA_MCC_1 B.1.1.7 2021-02-13 280 Bavaria
LIN-Germany-B.1.1.317-20210602_DTA_MCC_38 B.1.1.317 2021-01-07 274 Bavaria
LIN-Germany-B.1.1.7-30660-20210602_DTA_MCC_1 B.1.1.7 2021-02-26 274 Rhineland-Palatinate
LIN-Germany-B.1.1.7-30660-20210602_DTA_MCC_1 B.1.1.7 2021-02-26 274 Saxony
LIN-Germany-B.1.1.7-18644-20210602_DTA_MCC_1 B.1.1.7 2021-02-18 259 Lower Saxony
LIN-Germany-B.1.1.7-27635-20210602_DTA_MCC_1 B.1.1.7 2021-02-22 243 Saxony-Anhalt
LIN-Germany-B.1.1.7-27635-20210602_DTA_MCC_1 B.1.1.7 2021-02-22 243
LIN-Germany-B.1.1.7-23525-20210602_DTA_MCC_1 B.1.1.7 2021-01-29 231 Bavaria
LIN-Germany-B.1.1.7-23525-20210602_DTA_MCC_1 B.1.1.7 2021-01-29 231 Bavaria
LIN-Germany-B.1.1.7-23525-20210602_DTA_MCC_1 B.1.1.7 2021-01-29 231 Bavaria
LIN-Germany-B.1.221-20210602_DTA_MCC_4 B.1.221.2 2020-03-21 229 Saarland
LIN-Germany-B.1.1.7-64316-20210602_DTA_MCC_1 B.1.1.7 2021-02-16 223 North Rhine-Westphalia
LIN-Germany-B.1.221-20210602_DTA_MCC_306 B.1.221 2020-10-17 222 Saarland
LIN-Germany-B.1.221-20210602_DTA_MCC_306 B.1.221 2020-10-17 222 Saarland
LIN-Germany-B.1.1.7-40790-20210602_DTA_MCC_1 B.1.1.7 2021-02-13 210 Bremen
LIN-Germany-B.1.1.7-40790-20210602_DTA_MCC_1 B.1.1.7 2021-02-13 210 Bremen
LIN-Germany-B.1.1.7-40790-20210602_DTA_MCC_1 B.1.1.7 2021-02-13 210 Bremen
LIN-Germany-B.1.351-20210602_DTA_MCC_1624 B.1.351 2021-02-04 205 Saarland
LIN-Germany-B.1.351-20210602_DTA_MCC_1624 B.1.351 2021-02-04 205 Saarland
LIN-Germany-B.1.1.7-54346-20210602_DTA_MCC_1 B.1.1.7 2021-03-08 191 Baden-Wurttemberg
LIN-Germany-B.1.1.7-60099-20210602_DTA_MCC_1 B.1.1.7 2021-02-25 188 Thuringia
LIN-Germany-B.1.1.7-17101-20210602_DTA_MCC_1 B.1.1.7 2021-02-19 186 Hamburg
LIN-Germany-B.1.1.7-17101-20210602_DTA_MCC_1 B.1.1.7 2021-02-19 186 Hamburg
LIN-Germany-B.1.1.7-53110-20210602_DTA_MCC_1 B.1.1.7 2021-03-05 183 North Rhine-Westphalia
LIN-Germany-B.1.1.7-53110-20210602_DTA_MCC_1 B.1.1.7 2021-03-05 183 North Rhine-Westphalia
LIN-Germany-B.1.1.7-53110-20210602_DTA_MCC_1 B.1.1.7 2021-03-05 183 North Rhine-Westphalia
LIN-Germany-B.1.1.7-62408-20210602_DTA_MCC_1 B.1.1.7 2021-01-21 173 Hesse
LIN-Germany-B.1.1.7-26692-20210602_DTA_MCC_1 B.1.1.7 2021-02-27 170 Baden-Wurttemberg
LIN-Germany-A-20210602_DTA_MCC_68 A 2020-03-14 144 Hamburg
LIN-Germany-B.1.1.317-20210602_DTA_MCC_63 B.1.1.317 2021-01-22 142 Bavaria
LIN-Germany-B.1.1.7-4662-20210602_DTA_MCC_1 B.1.1.7 2021-02-19 142 Thuringia
LIN-Germany-B.1.1.7-36198-20210602_DTA_MCC_1 B.1.1.7 2021-03-02 139 Baden-Wurttemberg
LIN-Germany-B.1.221-20210602_DTA_MCC_920 B.1.221 2020-10-01 139 Saarland
LIN-Germany-B.1.1.7-2546-20210602_DTA_MCC_1 B.1.1.7 2021-03-26 136 North Rhine-Westphalia
LIN-Germany-B.1.1.7-8475-20210602_DTA_MCC_1 B.1.1.7 2021-03-04 131 North Rhine-Westphalia
LIN-Germany-B.1.221-20210602_DTA_MCC_90 B.1.221 2020-10-19 131 Saarland

Earliest transmission lineages

Illustration of the time course of the 50 earliest Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 earliest Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Newest transmission lineages

Illustration of the time course of the 50 most recent (by TMRCA) Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 most recent (by TMRCA) Dusseldorf transmission lineages in our dataset. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Longest periods of cryptic circulation

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest period of cryptic circulation. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest period of cryptic circulation. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Longest sampling period

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest sampling duration (from earliest to most recently collected genome). Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest sampling duration (from earliest to most recently collected genome). Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Longest unobserved period before reactivating

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest unobserved period before reemerging. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Illustration of the time course of the 50 Dusseldorf transmission lineages in our dataset with the longest unobserved period before reemerging. Each row is a transmission lineage. Dots are genome sampling times and boxes show the range of sampling times for each transmission lineage (sampling duration). Asterisks show the TMRCA of each lineage. On the right, n indicates the number of Dusseldorf genomes in the lineage and the duration of lineage detection (time between the lineage’s oldest and most recent genomes). Sampling times of the first 500 SARS-CoV-2 genomes collected in the Dusseldorf have been obscured.

Session info

## R version 4.0.3 (2020-10-10)
## Platform: x86_64-conda-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 8 (jessie)
## 
## Matrix products: default
## BLAS/LAPACK: /home/hforoughmand/miniconda3/envs/r4-base/lib/libopenblasp-r0.3.12.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] parallel  stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] maptools_1.1-1    colorspace_2.0-0  raster_3.4-13     sp_1.4-5         
##  [5] viridis_0.5.1     viridisLite_0.3.0 stringr_1.4.0     knitr_1.31       
##  [9] gplots_3.1.1      plyr_1.8.6        phytools_0.7-70   maps_3.3.0       
## [13] ggtree_2.4.1      ggsci_2.9         ggplot2_3.3.3     treeio_1.14.3    
## [17] rjson_0.2.20      beastio_0.3.3     tidytree_0.3.3    ape_5.4-1        
## [21] lubridate_1.7.10  dplyr_1.0.5       tictoc_1.0       
## 
## loaded via a namespace (and not attached):
##  [1] sass_0.3.1              tidyr_1.1.3             jsonlite_1.7.2         
##  [4] tmvnsim_1.0-2           gtools_3.8.2            bslib_0.2.4            
##  [7] expm_0.999-6            BiocManager_1.30.12     rvcheck_0.1.8          
## [10] highr_0.8               yaml_2.2.1              numDeriv_2016.8-1.1    
## [13] pillar_1.5.1            lattice_0.20-41         glue_1.4.2             
## [16] quadprog_1.5-8          phangorn_2.6.2          digest_0.6.27          
## [19] RColorBrewer_1.1-2      htmltools_0.5.1.1       Matrix_1.3-2           
## [22] pkgconfig_2.0.3         purrr_0.3.4             patchwork_1.1.1        
## [25] scales_1.1.1            tibble_3.1.0            combinat_0.0-8         
## [28] generics_0.1.0          ellipsis_0.3.2          withr_2.4.1            
## [31] lazyeval_0.2.2          mnormt_2.0.2            magrittr_2.0.1         
## [34] crayon_1.4.1            evaluate_0.14           fansi_0.4.2            
## [37] nlme_3.1-152            MASS_7.3-53.1           foreign_0.8-81         
## [40] tools_4.0.3             lifecycle_1.0.0         aplot_0.0.6            
## [43] munsell_0.5.0           plotrix_3.8-1           jquerylib_0.1.3        
## [46] compiler_4.0.3          clusterGeneration_1.3.7 caTools_1.18.2         
## [49] tinytex_0.31            rlang_0.4.10            grid_4.0.3             
## [52] igraph_1.2.6            bitops_1.0-6            rmarkdown_2.7          
## [55] gtable_0.3.0            codetools_0.2-18        R6_2.5.0               
## [58] gridExtra_2.3           utf8_1.2.1              fastmatch_1.1-0        
## [61] KernSmooth_2.23-18      stringi_1.5.3           Rcpp_1.0.6             
## [64] vctrs_0.3.8             scatterplot3d_0.3-41    tidyselect_1.1.0       
## [67] xfun_0.22               coda_0.19-4